The DOI matches its Crossref record; 84 of the 90 references it cites were found in a registry or an index.
Prey-Capture Behavior in Gymnotid Electric Fish: Motion Analysis and Effects of water Conductivity
Abstract
Animals can actively influence the content and quality of sensory information they acquire from the environment through the positioning of peripheral sensory surfaces. This study investigated receptor surface positioning during prey-capture behavior in weakly electric gymnotiform fish of the genus Apteronotus. Infrared video techniques and three-dimensional model-based tracking methods were used to provide quantitative information on body position and conformation as black ghost (A. albifrons) and brown ghost (A. leptorhynchus) knifefish hunted for prey (Daphnia magna) in the dark. We found that detection distance depends on the electrical conductivity of the surrounding water. Best performance was observed at low water conductivity (2.8 cm mean detection distance and 2 % miss rate at 35 microS cm(-)(1), A. albifrons) and poorest performance at high conductivity (1.5 cm mean detection distance and 11 % miss rate at 600 microS cm(-)(1), A. albifrons). The observed conductivity-dependence implies that nonvisual prey detection in Apteronotus is likely to be dominated by the electrosense over the range of water conductivities experienced by the animal in its natural environment. This result provides the first evidence for the involvement of electrosensory cues in the prey-capture behavior of gymnotids, but it leaves open the possibility that both the high-frequency (tuberous) and low-frequency (ampullary) electroreceptors may contribute. We describe an electrosensory orienting response to prey, whereby the fish rolls its body following detection to bring the prey above the dorsum. This orienting response and the spatial distribution of prey at the time of detection highlight the importance of the dorsal surface of the trunk for electrosensory signal acquisition. Finally, quantitative analysis of fish motion demonstrates that Apteronotus can adapt its trajectory to account for post-detection motion of the prey, suggesting that it uses a closed-loop adaptive tracking strategy, rather than an open-loop ballistic strike strategy, to intercept the prey.
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“This was not fully understood until prey capture behavior was automatically tracked in three dimensions, and then an entire suite of empirically validated models was used to compute the neuronal signal going to the brain over the course of prey capture behavior (MacIver et al., 2001;Nelson and MacIver, 1999;Snyder et al., 2007).”
From Neuroscience Needs Behavior: Correcting a Reductionist Bias (2017) · cites this paper as MacIver et al., 2001
Citations
Cites
Das Reafferenzprinzip: Wechselwirkungen zwischen Zentralnervensystem und Peripherie
von Holst, E., & Mittelstaedt, H. (1950) · Naturwissenschaften · doi:10.1007/bf00622503 · Cited by 2,655
Surround-screen projection-based virtual reality
Cruz‐Neira, C., Sandin, D. J., & DeFanti, T. A. (1993) · ACM SIGGRAPH Conference (SIGGRAPH) · doi:10.1145/166117.166134 · Cited by 2,400
The CAVE: audio visual experience automatic virtual environment
Cruz‐Neira, C., Sandin, D. J., DeFanti, T. A., Kenyon, R. V., & Hart, J. C. (1992) · Communications of the ACM · doi:10.1145/129888.129892 · Cited by 1,773
Animal Behaviour: A Synthesis of Ethology and Comparative Psychology
Cullen, J. M., & Hinde, R. A. (1968) · Journal of Animal Ecology · doi:10.2307/3093 · Cited by 846
The Amazon : limnology and landscape ecology of a mighty tropical river and its basin
Sioli, H. (1984) · Medical Entomology and Zoology · Cited by 665
Animal Behavior: A Synthesis of Ethology and Comparative Psychology
Stokes, A. W., & Hinde, R. A. (1967) · Journal of Wildlife Management · doi:10.2307/3798339 · Cited by 596
On the Function and Evolution of Electric Organs in Fish
Lissmann, H. W. (1958) · Journal of Experimental Biology · doi:10.1242/jeb.35.1.156 · Cited by 553
Breder, C. M. (1926) · Zoologica scientific contributions of the New York Zoological Society · doi:10.5962/p.203769 · Cited by 514
The Mechanosensory Lateral Line: Neurobiology and Evolution
Coombs, S., Görner, P., & Münz, H. (2011) · Cited by 430
Möller, P. (1995) · Chapman & Hall eBooks · Cited by 364
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6 of the 90 references couldn’t be matched to a known paper.
Research works printed but not linked: 8
- Bastian, 1986, Electrolocation: behavior, anatomy and physiology, 577
- Crampton, 1998, Electric signal design and habitat preferences in a species rich assemblage of gymnotiform fishes from the Upper Amazon Basin, Ann. Acad. Bras. Ci., 70, 805
- Dunning, 1973, A quantitative and comparative analysis of the tonic electroreceptors of Gnathonemus, Gymnotus and Kryptopterus. PhD thesis, University of Minnesota
- Hagedorn, 1996, Species diversity of gymnotiform fishes in Manu Bioreserve, Pakitza, Perú, 483
- Hopkins, 1972, Patterns of electrical communication among gymnotid fish. PhD thesis, Rockefeller University
- Hopkins, 1997, A quantitative analysis of passive electrolocation behavior in electric fish
- Lissmann, 1961, Ecological studies on gymnotids, 215
- Zakon, 1986, The electroreceptive periphery, 103
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Engelmann, J., & Lucks, V. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-809324-5.24212-0
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Peters, K. J., & Lewis, J. E. (2026) · Biology Letters · doi:10.1098/rsbl.2025.0632
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Metadata
- Authors
- Maciver, M. A., Sharabash, N. M., & Nelson, M. E.
- Affiliations
- 1 The Neuroscience Program
- 2 Beckman Institute for Advanced Science and Technology
- University of Illinois Urbana-Champaign (US)
- Venue
- Journal of Experimental Biology
- Publisher
- The Company of Biologists
- Published
- 2001-02-01
- Volume
- 204
- Issue
- 3
- Pages
- 543-557
- ISSN
- 0022-0949 (ISSN-L)
- 1477-9145
- OpenAlex
- W2103225200
- Cited by
- 184
- References
- 90
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 7 · 2023: 7 · 2022: 1 · 2021: 5 · 2020: 6 · 2019: 12 · 2018: 6 · 2017: 10 · 2016: 8 · 2015: 7 · 2014: 16 · 2013: 14 · 2012: 15
- FWCI
- 6.90
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Experimental Biology (publishedVersion)
- PubMed (publishedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- National Institute of Mental Health (R01-MH49242, R01MH049242)
- Topics
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Fish biology, ecology, and behavior
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Ichthyology and Marine Biology
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Plant and Biological Electrophysiology Studies
- Keywords
- Apteronotus, black ghost knifefish, prey capture, water conductivity, Daphnia magna, body motion tracking, adaptive tracking
- MeSH terms
- Animals, Behavior, Animal, Locomotion, Sensory Receptor Cells, Static Electricity
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